"Taking Stock at FAccT": Using Participatory Design to Co-Create a Vision for the Fairness, Accountability and Transparency Community

ACM FAccT conference employed large-scale participatory design to democratize governance decisions around AI fairness, accountability, and transparency issues. The process combined in-person sessions, asynchronous polling, and community-authored statements to shape the conference agenda and organizational direction.

The FAccT conference represents a critical institutional response to the governance challenges posed by AI and machine learning technologies. By implementing participatory design processes, the conference organizers addressed a fundamental tension: how can venues that critique AI systems' societal impacts maintain legitimacy and democratic input from diverse stakeholders? This approach matters because it models how academic and policy institutions can institutionalize feedback mechanisms rather than relying on top-down decision-making.

The participatory design methodology itself—combining in-person CRAFT sessions with asynchronous Polis polling—addresses scalability challenges that typically limit community engagement in governance. Participants directly shaped substantive agendas by authoring and voting on statements, creating visible patterns of consensus, disagreement, and uncertainty. This democratization of governance at a major AI ethics venue signals broader institutional evolution within computer science academia.

For the AI governance ecosystem, this development matters because it demonstrates practical mechanisms for inclusive decision-making at scale. The approach proves particularly valuable for venues examining AI's societal impacts, where stakeholder diversity—academics, civil society, government representatives—creates competing priorities and perspectives. The methodology validates participatory approaches as operationally feasible rather than purely theoretical.

Looking forward, the case study's significance depends on adoption and replication. If other major conferences and institutions adopt similar participatory governance models, this could reshape how AI ethics conversations happen institutionally. The work advances large-scale participatory design theory by proving epistemological scalability, potentially influencing how AI governance forums operate globally.

• →ACM FAccT applied large-scale participatory design to democratize conference governance around AI ethics and policy.
• →The methodology combined in-person workshops, asynchronous polling, and community-authored statements to shape institutional direction.
• →Participatory design proved operationally feasible for scaling governance across diverse stakeholder groups in academic settings.
• →The approach models how AI criticism venues can maintain legitimacy through democratic institutional processes.
• →Successful implementation could influence governance practices across AI ethics conferences and policy forums globally.